long overdue spell checking

R/as_survey.r

@@ -102,7 +102,7 @@ as_survey.twophase2 <- function(.data, ...) {
 #'
 #' srvyr has updated it's standard evaluation semantics to match dplyr 0.7, so
 #' these underscore functions are no longer required (but are still supported
-#' for backward compatbility reasons). See \code{\link[dplyr]{se-deprecated}} or the
+#' for backward compatibility reasons). See \code{\link[dplyr]{se-deprecated}} or the
 #' dplyr vignette on programming (\code{vignette("programming", package =
 #' "dplyr")}) for more details.
 #' @name srvyr-se-deprecated

R/as_survey_rep.r

@@ -17,18 +17,18 @@
 #' @export
 #' @param .data A data frame (which contains the variables specified below)
 #' @param variables Variables to include in the design (default is all)
-#' @param repweights Variables specifying the replication weight varibles
+#' @param repweights Variables specifying the replication weight variables
 #' @param weights Variables specifying sampling weights
 #' @param type Type of replication weights
 #' @param combined_weights \code{TRUE} if the \code{repweights} already
 #' include the sampling weights. This is usually the case.
-#' @param rho Shrinkage factor fo rweights in Fay's method
+#' @param rho Shrinkage factor for weights in Fay's method
 #' @param bootstrap_average For \code{type = "bootstrap"}, if the bootstrap
 #' weights have been averaged, gives the number of iterations averaged over.
 #' @param scale,rscales Scaling constant for variance, see
 #' \code{\link[survey]{svrepdesign}} for more information.
 #' @param fpc,fpctype Finite population correction information
-#' @param mse if \code{TRUE}, compute varainces based on sum of squares
+#' @param mse if \code{TRUE}, compute variances based on sum of squares
 #' around the point estimate, rather than the mean of the replicates
 #' @param ... ignored
 #' @param compress if \code{TRUE}, store replicate weights in compressed form

R/as_survey_twophase.r

@@ -8,16 +8,16 @@
 #'
 #' @export
 #' @param .data A data frame (which contains the variables specified below)
-#' @param id list of two sets of variable names for sampling unit identifers
+#' @param id list of two sets of variable names for sampling unit identifiers
 #' @param strata list of two sets of variable names (or \code{NULLs}) for stratum identifiers
 #' @param probs list of two sets of variable names (or \code{NULLs}) for sampling probabilities
 #' @param weights Only for method = "approx", list of two sets of variable names (or \code{NULLs})
 #' for sampling weights
 #' @param fpc list of two sets of variables (or \code{NULLs} for finite population corrections
 #' @param subset bare name of a variable which specifies which observations are selected in phase 2
 #' @param method "full" requires (much) more memory, but gives unbiased variance estimates for
-#' general multistage designs at both phases. "simple" or "approx" use less memory, and is correect for
-#' designs with simple random sampling at phase one and stratifed randoms sampling at phase two. See
+#' general multistage designs at both phases. "simple" or "approx" use less memory, and is correct for
+#' designs with simple random sampling at phase one and stratified randoms sampling at phase two. See
 #' \code{\link[survey]{twophase}} for more details.
 #' @param ... ignored
 #' @return An object of class \code{tbl_svy}

R/group-by.r

@@ -47,7 +47,7 @@ group_vars.tbl_svy <- function(x) {
 #' On \code{tbl_svy} objects, \code{group_by} sets up the object for
 #' operations similar to those allowed in \code{\link[survey]{svyby}}.
 #' @param .data A tbl
-#' @param ... variables to gorup by. All tbls accept variable names, some will
+#' @param ... variables to group by. All tbls accept variable names, some will
 #' also accept functions of variables. Duplicated groups will be silently dropped.
 #' @param add By default, when \code{add = FALSE}, \code{group_by} will override
 #' existing groups. To instead add to the existing groups, use \code{add = TRUE}

R/lazy_tbl.r

@@ -86,7 +86,7 @@ find_vars_to_collect <- function(var_names, expr) {
 
 #' Force computation of a database query
 #'
-#' \code{collect} retreives data from a database query (and when run
+#' \code{collect} retrieves data from a database query (and when run
 #' on a tbl_svy object adjusts weights accordingly). Use collect when
 #' you want to run a function from the survey package on a srvyr db
 #' backed object. \code{compute} stores results in a remote temporary

R/manip.r

@@ -75,7 +75,7 @@ filter_.tbl_svy <- function(.data, ..., .dots) {
 #' \code{select} and \code{rename} keep or rename variables. See
 #' \code{\link[dplyr]{select}} for more details.
 #'
-#' \code{filter} keeps certain observaions. See \code{\link[dplyr]{filter}}
+#' \code{filter} keeps certain observations. See \code{\link[dplyr]{filter}}
 #' for more details.
 #'
 #' \code{arrange} is not implemented for \code{tbl_svy} objects. Nor are any
@@ -150,7 +150,7 @@ NULL
 
 #' Manipulate multiple columns.
 #'
-#' See \code{\link[dplyr]{summarize_all}} for more details. *_each functions will be depracated
+#' See \code{\link[dplyr]{summarize_all}} for more details. *_each functions will be deprecated
 #' in favor of *_all/*_if/*_at functions.
 #'
 #' @name summarise_all

R/srvyr.r

@@ -1,4 +1,4 @@
-#' svrvyr: A package for 'dplyr'-Like Syntax for Summary Statistics of Survey Data.
+#' srvyr: A package for 'dplyr'-Like Syntax for Summary Statistics of Survey Data.
 #'
 #' The srvyr package provides a new way of calculating summary statistics
 #' on survey data, based on the dplyr package. There are three stages to using

R/survey_count_tally.R

@@ -1,6 +1,6 @@
 #' Count/tally survey weighted observations by group
 #'
-#' Analagous to \code{\link[dplyr]{tally}} and count, calculates the survey weighted
+#' Analogous to \code{\link[dplyr]{tally}} and count, calculates the survey weighted
 #' count of observations. \code{survey_tally} will call \code{\link{survey_total}} empty (resulting
 #' in the count of each group) or on \code{wt} if it is specified (resulting in the
 #' survey weighted total of \code{wt}). \code{survey_count} is similar, but calls \code{group_by}

R/svy_context.R

@@ -1,4 +1,4 @@
-# Functions modelled on the tidyselect functions for telling functions within
+# Functions modeled on the tidyselect functions for telling functions within
 # summarize what the survey is. I think they are a little overly complex - I
 # can't really imagine having one already set and and setting another, but just
 # in case, I keep that code.

README.Rmd

@@ -40,7 +40,7 @@ install.packages("srvyr")
 
 ## Example usage
 
-First, describe the variables that define the survey's stucture with the function
+First, describe the variables that define the survey's structure with the function
 `as_survey()`with the bare column names of the names that you would use in functions
 from the survey package like `survey::svydesign()`, `survey::svrepdesign()` or 
 `survey::twophase()`.
@@ -89,7 +89,7 @@ summary(my_model)
 
 > 1. Yay!
 > 
-> --<cite>Thomas Lumley, [in the Biased and Inefficent blog](http://notstatschat.tumblr.com/post/161225885311/pipeable-survey-analysis-in-r)</cite>
+> --<cite>Thomas Lumley, [in the Biased and Inefficient blog](http://notstatschat.tumblr.com/post/161225885311/pipeable-survey-analysis-in-r)</cite>
 
 
 ## Contributing

README.md

@@ -33,9 +33,9 @@ install.packages("srvyr")
 
 ## Example usage
 
-First, describe the variables that define the survey’s stucture with the
-function `as_survey()`with the bare column names of the names that you
-would use in functions from the survey package like
+First, describe the variables that define the survey’s structure with
+the function `as_survey()`with the bare column names of the names that
+you would use in functions from the survey package like
 `survey::svydesign()`, `survey::svrepdesign()` or `survey::twophase()`.
 
 ``` r
@@ -125,7 +125,7 @@ summary(my_model)
 
 > 1.  Yay\!
 > 
-> –<cite>Thomas Lumley, [in the Biased and Inefficent
+> –<cite>Thomas Lumley, [in the Biased and Inefficient
 > blog](http://notstatschat.tumblr.com/post/161225885311/pipeable-survey-analysis-in-r)</cite>
 
 ## Contributing

vignettes/extending-srvyr.Rmd

@@ -31,14 +31,14 @@ survey objects work. If you'd like more explanation, please let me know on
 [github](https://github.com/gergness/srvyr)!
 
 ## Translating from survey to srvyr
-srvyr implements the "survey tatistics" functions from the survey package. Some examples
+srvyr implements the "survey statistics" functions from the survey package. Some examples
 are the svymean, svytotal, svyciprop, svyquantile and svyratio all return a
 `svystat` object which usually prints out the estimate and its standard error
 and other estimates of the variance can be calculated from it. In srvyr, these
 estimates are created inside of a summarize call and the variance estimates are
 specified at the same time.
 
-The combination of srvyr's group_by and summarize is analagous to the `svyby`
+The combination of srvyr's group_by and summarize is analogous to the `svyby`
 function that performs one of the survey statistic function and performs it on
 multiple groups.
 
@@ -66,7 +66,7 @@ should be:
 srvyr now exports several functions that can help convert functions designed
 for the survey package to this format.
 
-- `current_svy()` - This function, modelled after `dplyr::current_vars()`,
+- `current_svy()` - This function, modeled after `dplyr::current_vars()`,
   is a hidden way to send the survey object to the object (by hidden, I mean 
   that the user doesn't have to specify the survey in the arguments of their
   function call). To use it, have an argument in your functions that

vignettes/srvyr-database.Rmd

@@ -33,11 +33,11 @@ This vignette shows the basics of how to use srvyr with databases.
 It is based on analysis from the wonderful resource asdfree 
 ( [website](http://asdfree.com/) and [github](https://github.com/ajdamico/asdfree) ). 
 Many thanks to [ajdamico](http://github.com/ajdamico) and collaborators. 
-Specifically, I have adpated code from [American Community Survey - 2011 single year analysis](https://github.com/ajdamico/asdfree/blob/d0b965e9672161da086e30471760d08281b74343/American%20Community%20Survey/2011%20single-year%20-%20analysis%20examples.R) and the associated data preparation scripts. 
+Specifically, I have adapted code from [American Community Survey - 2011 single year analysis](https://github.com/ajdamico/asdfree/blob/d0b965e9672161da086e30471760d08281b74343/American%20Community%20Survey/2011%20single-year%20-%20analysis%20examples.R) and the associated data preparation scripts. 
 
 ## Database Setup ##
 In order to focus on srvyr and databases, we start with a prepared dataset. The full code 
-is avaliable [on Github](https://github.com/gergness/srvyr/blob/master/vignettes/save_acs_data.R), and the high level description of what it does is:
+is available [on Github](https://github.com/gergness/srvyr/blob/master/vignettes/save_acs_data.R), and the high level description of what it does is:
 
 - Download data from acs website (currently only Alaska and Hawaii to save time, 
 though it would be easy to adapt to download to all 50 states and Puerto Rico). 
@@ -161,7 +161,7 @@ specific database packages, like `RSQLite`.
 
 ## Srvyr Setup ##
 Srvyr commands are nearly identical to old. The only difference for setup is that you 
-need a variable that uniquely identifieds each row in the database (uid). 
+need a variable that uniquely identifies each row in the database (uid). 
 
 ```{r}
 acs_m_db_svy <- acs_m_db %>% 
@@ -193,8 +193,8 @@ Analysis commands from srvyr are also similar to ones that work on local data.fr
 The main differences come from the issues discussed above about explicitly creating variables
 difficulties in translating R commands, and variable types. 
 
-The following anlaysis is based on the asdfree analysis and shows some basi analysis on
-the total populaiton, insurance coverage, age and sex. 
+The following analysis is based on the asdfree analysis and shows some basic analysis on
+the total population, insurance coverage, age and sex. 
 
 ```{r}
 # You can calculate the population of the united states #